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Found 3 papers, 2 papers with code
Moment Matching Deep Contrastive Latent Variable Models
In the contrastive analysis (CA) setting, machine learning practitioners are specifically interested in discovering patterns that are enriched in a target dataset as compared to a background dataset generated from sources of variation irrelevant to the task at hand.
Learning Deep Attribution Priors Based On Prior Knowledge
In real-world problems we often have sets of additional information for each feature that are predictive of that feature's importance to the task at hand.
Defending against Adversarial Images using Basis Functions Transformations
We study the effectiveness of various approaches that defend against adversarial attacks on deep networks via manipulations based on basis function representations of images.
